{"id":"W2198732287","doi":"10.1016/j.jtbi.2007.08.021","title":"Addendum to “Modeling human mortality using mixtures of bathtub shaped failure distributions”","year":2007,"lang":"en","type":"letter","venue":"Journal of Theoretical Biology","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Mixture model; Outlier; Mixture distribution; Expectation–maximization algorithm; Cluster analysis; Multivariate statistics; Computer science; Applied mathematics; Mathematics; Algorithm; Statistics; Probability density function; Maximum likelihood","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.004261089,0.0003573658,0.001038576,0.0005732887,0.0004007437,0.00006811451,0.001194351,0.001269049,0.0005453553],"category_scores_gemma":[0.0008610266,0.0002939635,0.0007519965,0.0005174728,0.002345834,0.00009605521,0.0002099618,0.001906761,0.000006906987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000231836,"about_ca_system_score_gemma":0.000189175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004363992,"about_ca_topic_score_gemma":0.0001983975,"domain_scores_codex":[0.9951905,0.001225428,0.001482213,0.0004017705,0.000852681,0.0008474077],"domain_scores_gemma":[0.997254,0.0003529555,0.0009536596,0.0004179879,0.0007993969,0.0002219774],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001061015,0.0002134139,0.008953756,0.0001602384,0.0009882061,0.000370339,0.0007526126,0.00008934832,0.001832012,0.8413887,0.1447592,0.0003860845],"study_design_scores_gemma":[0.001141125,0.0010208,0.001747297,0.0007670211,0.002006409,0.00004965979,0.001289315,0.0004548685,0.0004152312,0.6515138,0.3379179,0.001676606],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5868985,0.001033916,0.1099961,0.2857628,0.005308277,0.001463684,0.0008192164,0.00009358591,0.008623871],"genre_scores_gemma":[0.9570897,0.00007231303,0.002287754,0.03313946,0.007286557,0.00000354786,0.00006711667,0.00003106896,0.00002254826],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3701911,"threshold_uncertainty_score":0.9999512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05140405249510186,"score_gpt":0.3826258845561444,"score_spread":0.3312218320610426,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}